Semantic operators: LLM data processing at scale needs full-stack rethink
CShorten30 · x · 2026-09-24
- lianapatel uses "jev for semantic operators" to argue that LLM data processing at scale requires rethinking the entire stack, including model architectures and learning algorithms.
- EricMao06 credits the lotus paper for many borrowed concepts, calling the idea ahead of its time.
- New work and further thoughts are promised soon; readers are pointed to lotus and star projects.
More from Research
- Programmable quantum photonic processor runs in orbit for the first time on a nanosatellite — jwt0625 · 2026-09-24
- WFM paper: agents need dense LLM-Wiki memory, not sparse knowledge-graph triples — maier_ak · 2026-09-24
- Sparse knowledge graphs break down when assistants plan across days, author argues — maier_ak · 2026-09-24
- Agent memory system runs up to four self-reflection rounds at inference — maier_ak · 2026-09-24
- WFM proposes hybrid graph keeping both full-text passages and crisp KG edges — maier_ak · 2026-09-24
- From Sparse Triples to Dense Wiki: Why Agents Need Better Memory — maier_ak · 2026-09-24